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The socio-economic patterning of survey participation and non-response error in a multilevel study of food purchasing behaviour: area- and individual-level characteristics

Published online by Cambridge University Press:  02 January 2007

Gavin Turrell ,
Carla Patterson ,
Brian Oldenburg ,
Trish Gould  and
Marie-Andree Roy
Gavin Turrell*
Affiliation:
Queensland University of Technology, School of Public Health, Victoria Park Road, Kelvin Grove, Brisbane, Queensland 4059, Australia
Carla Patterson
Affiliation:
Queensland University of Technology, School of Public Health, Victoria Park Road, Kelvin Grove, Brisbane, Queensland 4059, Australia
Brian Oldenburg
Affiliation:
Queensland University of Technology, School of Public Health, Victoria Park Road, Kelvin Grove, Brisbane, Queensland 4059, Australia
Trish Gould
Affiliation:
Queensland University of Technology, School of Public Health, Victoria Park Road, Kelvin Grove, Brisbane, Queensland 4059, Australia
Marie-Andree Roy
Affiliation:
Queensland University of Technology, School of Public Health, Victoria Park Road, Kelvin Grove, Brisbane, Queensland 4059, Australia
*
*Corresponding author: Email g.turrell@qut.edu.au
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Abstract

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Objective:

To undertake an assessment of survey participation and non-response error in a population-based study that examined the relationship between socio-economic position and food purchasing behaviour.

Design and setting:

The study was conducted in Brisbane City (Australia) in 2000. The sample was selected using a stratified two-stage cluster design. Respondents were recruited using a range of strategies that attempted to maximise the involvement of persons from disadvantaged backgrounds: respondents were contacted by personal visit and data were collected using home-based face-to-face interviews; multiple call-backs on different days and at different times were used; and a financial gratuity was provided.

Participants:

Non-institutionalised residents of private dwellings (n = 1003), located in 50 small areas that differed in their socio-economic characteristics.

Results:

Rates of survey participation – measured by non-contacts, exclusions, dropped cases, response rates and completions – were similar across areas, suggesting that residents of socio-economically advantaged and disadvantaged areas were equally likely to be recruited. Individual-level analysis, however, showed that respondents and non-respondents differed significantly in their sociodemographic and food purchasing characteristics: non-respondents were older, less educated and exhibited different purchasing behaviours. Misclassification bias probably accounted for the inconsistent pattern of association between the area- and individual-level results. Estimates of bias due to non-response indicated that although respondents and non-respondents were qualitatively different, the magnitude of error associated with this differential was minimal.

Conclusions:

Socio-economic position measured at the individual level is a strong and consistent predictor of survey non-participation. Future studies that set out to examine the relationship between socio-economic position and diet need to adopt sampling strategies and data collection methods that maximise the likelihood of recruiting participants from all points on the socio-economic spectrum, and particularly persons from disadvantaged backgrounds. Study designs that are not sensitive to the difficulties associated with recruiting a socio-economically representative sample are likely to produce biased estimates (underestimates) of socio-economic differences in the dietary outcome being investigated.

Keywords

Survey participationNon-response errorSocio-economic positionFood purchasing
Type
Research Article
Information
Public Health Nutrition , Volume 6 , Issue 2 , April 2003 , pp. 181 - 189
Copyright
Copyright © CABI Publishing 2003

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